AI NewsSalesforce is crowdsourcing its AI roadmap — with customers

Salesforce is crowdsourcing its AI roadmap — with customers

10:21 PM IST · April 30, 2026

Artificial intelligence continues to advance at a dizzying clip, forcing enterprises to develop and release new products quicker than ever or risk becoming irrelevant to a faster-moving competitor. Salesforce believes it has found a strategy that allows it to keep up even if it isn’t clear where AI is headed next. The customer management software giant is crowdsourcing its AI roadmap in real time. Salesforce is certainly not the only company to work intimately with its customers for feedback on its products. However, it’s notable considering the sheer size of the company, the pace of new product launches or fixes to existing ones, and the granular level of these relationships. These aren’t annual or even quarterly discussions. Salesforce is meeting with some customers as often as once a week. “The 18,000 customers are a wellspring of information and a wealth of information that is really needed to get to customer success,” Jayesh Govindarajan, executive vice president at Salesforce AI, told TechCrunch in a recent interview. “The stack that we’ve built that has resonated with these customers. Over time we can get context to be better, and as it gets better, and LLMs get better, agent systems do more and more fully autonomous behaviors. That’s a long running innovation track and we’re going to invest in that.” Salesforce was one of the first companies to launchAI agent management softwarein late 2024 before agentic AI started to dominate headlines the following year. The company has since doubled down and continues to release new products forvoice AIandSlackat a rapid pace. Salesforce credits its customers for the rate of its product releases. The company told TechCrunch that by letting its customers lead the way it is able to build an AI product roadmap that can quickly react to where AI technology is headed. When large language models were introduced, enterprises naturally wanted to jump on the technology but didn’t have the last-mile tech needed to fully use LLMs, Muralidhar Krishnaprasad, the president and chief technology officer of Salesforce engineering, told TechCrunch. The need for that last-mile tech is what sparked Salesforce to launch its agent management platform Agentforce, Jayesh Govindarajan, executive vice president at Salesforce AI, said in a recent interview. From there, the company developed a bottom-up strategy led by themes — including agent context, observability, and deterministic controls, among others — as opposed to specific product timelines. This approach uses direct feedback from rotating groups of customers to build products with the assumption that other enterprises will have similar needs. “The innovation that we’ve brought, they are direct result of us working with a vast number of these customers and then classifying the problems they see in the real world,” Govindarajan said. ‘Then [we break] that down and say, which of this can be solved at the LLM layer, which cannot? And for things that we cannot solve at the LLM layer, we need to build that sort of agentic operating system components around the LLMs to be able to go do that.” Working so closely with customers’ engineering teams allows Salesforce to fix problems quickly before the technology evolves past them. “We can’t wait three months or six months to get feedback, and then go figure out another six months of work,” Krishnaprasad said. “We are literally reacting to it, week by week, month by month. That’s been a big change. Now we push code, pretty fast, and we have various sorts of gates to try out new features, get earlier feedback before we release it broadly as well. So those are all changes that we had to do to kind of accommodate this rapid change in this environment.” Engine, a travel management platform, is one of the companies within Salesforce’s customer feedback loop. And it’s not a casual relationship. The company’s operations team meets with Salesforce weekly, according to Engine founder and CEO Elia Wallen. Through the partnership, Engine gets access to AI tools before they’re released. Wallen said the access helps Engine stay competitive and get more value out of these tools than it would otherwise. The relationship goes both ways. Wallen said he’s seen feedback from Engine get implemented into Salesforce tools. For example, Wallen said he instructed an AI voice agent to book him a hotel in Chicago. He thought the voice and interaction felt a bit unnatural and shared that with Salesforce. Shortly after, the agent had been changed and the company’s A/B tests started showing better results. “If somebody is willing to actually help curate and build products that we need, they can help us better and really understand our problem and how they can solve it,” Wallen said. “For us, it’s fantastic to actually be invited into a thing like that, because we can influence the product.” This strategy also allows the company to roll out solutions and workflows built by users to its broader customer base too. Federal credit union PenFed has been able to slim down its tech stack by working closely with Salesforce, Shree Reddy, the company’s chief innovation officer and executive vice president told TechCrunch. “We invest our time, energy into the platforms that are more strategic, and we obviously spend a lot more time on this relationship,” Reddy said about Salesforce. “That investment has yielded good results in terms of strengthening that partnership that’s influencing each other, and what we see is the best value add mutually to both organizations.” Reddy said PenFed developed an IT service management (ITSM) workflow on its own using existing tools and agents in Agentforce that worked well for the company. Salesforce was able to see that success and roll out the tool into the broader platform for other enterprises to use as well. The downside to this approach is that it relies on the classic service sentiment that the customer is always right. Salesforce is hoping they are despite many enterprises still figuring outwhat role AI will playin their business, and many having yet tofind value from the tech. As a result, they might not be the best source for long-term product development. Plus, being willing to test and preview technology in beta now doesn’t necessarily translate to long-term usage habits or future software contracts either. The company also takes this bottom-up approach internally. Govindarajan said Salesforce employees are the biggest users of its AI tools. The company also shifted labor and resources at the start of the AI boom. When ChatGPT was released, Salesforce moved around teams and resources to create a new AI team — a strategy the company has found successful during different innovation waves in the past, Krishnaprasad said. “As the technology changes, we never know what’s going to come out a month from now,” Krishnaprasad said. “We will adapt to it. And that’s what we did all of last year. If you think about it, agents weren’t even in terminology when you look back a year and a half ago. And then we had to go react to it. We had to go react to all the advances, and we had to react to our customers.”